Deexaggeration

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Abstract

We introduce a new task in hyperbole processing, deexaggeration, which concerns the recovery of the meaning of what is being exaggerated in a hyperbolic sentence in the form of a structured representation. In this paper, we lay the groundwork for the computational study of understanding hyperbole by (1) defining a structured representation to encode what is being exaggerated in a hyperbole in a non-hyperbolic manner, (2) annotating the hyperbolic sentences in two existing datasets, HYPO and HYPO-cn, using this structured representation, (3) conducting an empirical analysis of our annotated corpora, and (4) presenting preliminary results on the deexaggeration task.

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APA

Kong, L., Li, C., & Ng, V. (2022). Deexaggeration. In IJCAI International Joint Conference on Artificial Intelligence (pp. 4185–4192). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2022/581

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